# FPSIR predicts clinical therapeutic responses and survival outcomes in patients with metastatic colorectal cancer undergoing first-line bevacizumab-containing chemotherapy

**Authors:** Ya-Nan Li, Feng-Wen Deng, Tian-Qi Lan, Ying Lu, Lin Xiang, Guo-Bin Song, Tian Peng, Xue-Xin Cheng, Hou-Qun Ying

PMC · DOI: 10.3389/fimmu.2026.1683928 · Frontiers in Immunology · 2026-01-27

## TL;DR

FPSIR, a new biomarker combining inflammatory indicators, predicts treatment response and survival in metastatic colorectal cancer patients receiving bevacizumab-based therapy.

## Contribution

FPSIR is introduced as a novel predictive biomarker for bevacizumab-containing chemotherapy in metastatic colorectal cancer.

## Key findings

- FPSIR was independently associated with progression-free survival in both discovery and validation cohorts.
- FPSIR predicted worse 2-year overall survival in metastatic colorectal cancer patients.
- FPSIR-based survival nomograms effectively estimated PFS and OS with high accuracy.

## Abstract

Identifying patients who are most likely to benefit from the combination of bevacizumab and chemotherapy (Bev/CT) is essential for the optimal management of metastatic colorectal cancer (mCRC). The aim of this study is to investigate the utility of chronic inflammatory biomarkers in predicting clinical response to Bev/CT and outcomes in patients with mCRC.

This study enrolled 364 patients with mCRC undergoing first-line Bev/CT therapy. The patients were randomly assigned to discovery (n=249) and validation (n=115) cohorts, maintaining an approximate 2:1 ratio. Two machine learning algorithms, least absolute shrinkage and selection operator (LASSO)-penalized Cox regression and random survival forest (RSF), were employed to identify significant inflammatory biomarkers. Logistic regression, Kaplan-Meier survival analysis, and Cox regression analyses were conducted to evaluate the associations between the clinical outcomes and a product of fibrinogen-pre-albumin ratio and systematic inflammatory ratio (SIR) (FPSIR) and clinical outcomes. The primary endpoints included clinical disease control rate (DCR) and progression-free survival (PFS), 2-year overall survival (OS) was designated as a secondary endpoint.

Following the integration of inflammatory biomarkers identified through the LASSO and RSF algorithms, FPSIR was independently associated with PFS in both the discovery (plog-rank<0.001, adjusted HR = 1.90, 95%CI=1.40-2.57) and validation cohorts (plog-rank=0.01, adjusted HR = 1.89, 95%CI=1.21-2.98). Furthermore, FPSIR-H was significantly associated with worse 2-year OS in the two cohorts (discovery cohort: plog-rank<0.001, adjusted HR = 2.15, 95%CI=1.49-3.10; validation cohort: plog-rank=0.02, adjusted HR = 1.93, 95%CI=1.06-3.51). Survival nomograms that incorporated CEA, CA19–9 and FPSIR (CCF) score, along with peritoneum metastases, number of metastatic sites, surgical intervention, and treatment regimens could effectively estimate 2-year PFS (AUC = 0.83) and 18-month OS (AUC = 0.71) in the discovery cohort, demonstrating robust performance in the validation cohort (AUC = 0.76 and 0.75 for PFS and OS, respectively). Elevated FPSIR was correlated with diminished DCR in Bev/CT therapy (p < 0.01, adjusted OR = 2.24, 95% CI = 1.27-3.96). Serial measurements of FPSIR exhibited dynamic changes that effectively monitored the efficacy of Bev/CT treatment.

Pretreatment FPSIR was identified as a robust biomarker for predicting clinical efficacy and prognosis in mCRC patients receiving first-line Bev/CT, providing a promising strategy to address the long-standing challenge of treatment stratification.

## Full-text entities

- **Genes:** FGB (fibrinogen beta chain) [NCBI Gene 2244] {aka HEL-S-78p}, ALB (albumin) [NCBI Gene 213] {aka FDAHT, HSA, PRO0883, PRO0903, PRO1341}
- **Diseases:** colorectal cancer (MESH:D015179), inflammatory (MESH:D007249), metastases (MESH:D009362)
- **Chemicals:** bevacizumab (MESH:D000068258)
- **Species:** Homo sapiens (human, species) [taxon 9606]

## Full text

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## Figures

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## References

42 references — full list in the complete paper: https://tomesphere.com/paper/PMC12886467/full.md

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Source: https://tomesphere.com/paper/PMC12886467